Using Grey Forecasting Model to Analyze the Social and Economic Factors in Predicting the Traffic Volume of Public Transportation Systems / 影響大眾運輸系統運量之社會經濟因素灰預測模式之研究

碩士 / 中華大學 / 運輸科技與物流管理學系碩士班 / 102 / The waves of economic growth and social development are the main factors in predicting the future traffic volume, and we often input the historical data into the forecasting model. When it comes to predict the long-term future traffic volume, we have to establish a new forecasting model for the economic growth and social development. In this way, the data processing of traffic volume forecasting model will be difficult to proceed. By reviewing the economic growth and social development’s forecasting model, and using the authentic data to compare, this study aims at presenting the fine suggestion for the traffic volume research. This study uses Grey forecasting, Simple Regression, and Time series to analyze the data of economic growth and social development, and discusses the final data’s accuracy among Grey forecasting, Simple Regression, and Time series. This study’s result indicates that comparing with Grey forecasting (ten set statistic), Simple Regression, and Time series, using Grey forecasting (four set statistic) to analyze the data of economic growth and social development can get the optimization MAPE. The Mean Absolute Percentage Error (MAPE) of population is 0.02669%, oil price is 1.02411%, and GDP is 0.49157%. In conclusion, using Grey forecasting (four set statistic) can set up the fine forecasting model for analyzing the various data of economic growth and social development.

Identiferoai:union.ndltd.org:TW/102CHPI5425016
Date January 2014
CreatorsChang, Chun-Hung, 張俊鴻
ContributorsLo, Shih-Ching, 羅仕京
Source SetsNational Digital Library of Theses and Dissertations in Taiwan
Languagezh-TW
Detected LanguageEnglish
Type學位論文 ; thesis
Format48

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